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12 years 6 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis
CORR
2012
Springer
196views Education» more  CORR 2012»
12 years 3 months ago
PAC-Bayesian Policy Evaluation for Reinforcement Learning
Bayesian priors offer a compact yet general means of incorporating domain knowledge into many learning tasks. The correctness of the Bayesian analysis and inference, however, lar...
Mahdi Milani Fard, Joelle Pineau, Csaba Szepesv&aa...
GLOBECOM
2009
IEEE
14 years 2 months ago
Bayesian Cramer-Rao Bound for OFDM Rapidly Time-Varying Channel Complex Gains Estimation
Abstract—In this paper, we consider the Bayesian CramerRao bound (BCRB) for the dynamical estimation of multi-path Rayleigh channel complex gains in data-aided (DA) and non-dataa...
Hussein Hijazi, Laurent Ros
DCC
2007
IEEE
14 years 7 months ago
Bayesian Detection in Bounded Height Tree Networks
We study the detection performance of large scale sensor networks, configured as trees with bounded height, in which information is progressively compressed as it moves towards th...
Wee-Peng Tay, John N. Tsitsiklis, Moe Z. Win
UAI
1997
13 years 8 months ago
Robustness Analysis of Bayesian Networks with Local Convex Sets of Distributions
Robust Bayesian inference is the calculation of posterior probability bounds given perturbations in a probabilistic model. This paper focuses on perturbations that can be expresse...
Fabio Gagliardi Cozman